%global _empty_manifest_terminate_build 0 Name: python-SpaDecon Version: 1.1.2 Release: 1 Summary: SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning License: MIT License URL: https://github.com/kylepcoleman87/SpaDecon Source0: https://mirrors.aliyun.com/pypi/web/packages/fa/a0/96e2f8fba0e577948f7e7e948f31aa619968bd1ce0861f94ff392c341826/SpaDecon-1.1.2.tar.gz BuildArch: noarch Requires: python3-keras Requires: python3-pandas Requires: python3-numpy Requires: python3-scipy Requires: python3-scanpy Requires: python3-anndata Requires: python3-sklearn Requires: python3-tensorflow %description # SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning ### Kyle Coleman, Jian Hu, Amelia Schroeder, Edward B. Lee, Mingyao Li* SpaDecon is a semi-supervised learning-based method developed to perform cell-type deconvolution on spatially resolved transcriptomics (SRT) datasets. SpaDecon has been shown to provide accurate cell-type deconvolution results for both Spatial Transcriptomics (ST) and 10X Visium SRT datasets. Annotated scRNA-seq gene expression data from the same type of tissue as the SRT data are required for deconvolution. ![png](images/spadecon_workflow.png) ## SpaDecon Installation - SpaDecon installation requires a python version of at least 3.6. The version of python can be checked by: ```python import platform platform.python_version() ``` '3.7.11' We recommend creating and activating a new conda environment when installing the SpaDecon package. For instance, ```bash conda create -n SpaDecon python=3.7 conda activate SpaDecon ``` There are mulitple ways to install SpaDecon: - Install SpaDecon using PyPI: ```bash pip3 install SpaDecon ``` - Download and install SpaDecon package from GitHub: ```bash git clone https://github.com/kpcoleman/SpaDecon cd SpaDecon/ python3 setup.py install --user ``` ## Tutorial A markdown tutorial file can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/Tutorial.md A tutorial in the form of a jupyter notebook can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/tutorial.ipynb ## Software Requirements python >= 3.6 keras==2.2.4 pandas==1.2.4 numpy==1.20.1 scipy==1.6.2 scanpy==1.7.0 anndata==0.7.6 sklearn tensorflow==1.14.0 %package -n python3-SpaDecon Summary: SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning Provides: python-SpaDecon BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-SpaDecon # SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning ### Kyle Coleman, Jian Hu, Amelia Schroeder, Edward B. Lee, Mingyao Li* SpaDecon is a semi-supervised learning-based method developed to perform cell-type deconvolution on spatially resolved transcriptomics (SRT) datasets. SpaDecon has been shown to provide accurate cell-type deconvolution results for both Spatial Transcriptomics (ST) and 10X Visium SRT datasets. Annotated scRNA-seq gene expression data from the same type of tissue as the SRT data are required for deconvolution. ![png](images/spadecon_workflow.png) ## SpaDecon Installation - SpaDecon installation requires a python version of at least 3.6. The version of python can be checked by: ```python import platform platform.python_version() ``` '3.7.11' We recommend creating and activating a new conda environment when installing the SpaDecon package. For instance, ```bash conda create -n SpaDecon python=3.7 conda activate SpaDecon ``` There are mulitple ways to install SpaDecon: - Install SpaDecon using PyPI: ```bash pip3 install SpaDecon ``` - Download and install SpaDecon package from GitHub: ```bash git clone https://github.com/kpcoleman/SpaDecon cd SpaDecon/ python3 setup.py install --user ``` ## Tutorial A markdown tutorial file can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/Tutorial.md A tutorial in the form of a jupyter notebook can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/tutorial.ipynb ## Software Requirements python >= 3.6 keras==2.2.4 pandas==1.2.4 numpy==1.20.1 scipy==1.6.2 scanpy==1.7.0 anndata==0.7.6 sklearn tensorflow==1.14.0 %package help Summary: Development documents and examples for SpaDecon Provides: python3-SpaDecon-doc %description help # SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning ### Kyle Coleman, Jian Hu, Amelia Schroeder, Edward B. Lee, Mingyao Li* SpaDecon is a semi-supervised learning-based method developed to perform cell-type deconvolution on spatially resolved transcriptomics (SRT) datasets. SpaDecon has been shown to provide accurate cell-type deconvolution results for both Spatial Transcriptomics (ST) and 10X Visium SRT datasets. Annotated scRNA-seq gene expression data from the same type of tissue as the SRT data are required for deconvolution. ![png](images/spadecon_workflow.png) ## SpaDecon Installation - SpaDecon installation requires a python version of at least 3.6. The version of python can be checked by: ```python import platform platform.python_version() ``` '3.7.11' We recommend creating and activating a new conda environment when installing the SpaDecon package. For instance, ```bash conda create -n SpaDecon python=3.7 conda activate SpaDecon ``` There are mulitple ways to install SpaDecon: - Install SpaDecon using PyPI: ```bash pip3 install SpaDecon ``` - Download and install SpaDecon package from GitHub: ```bash git clone https://github.com/kpcoleman/SpaDecon cd SpaDecon/ python3 setup.py install --user ``` ## Tutorial A markdown tutorial file can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/Tutorial.md A tutorial in the form of a jupyter notebook can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/tutorial.ipynb ## Software Requirements python >= 3.6 keras==2.2.4 pandas==1.2.4 numpy==1.20.1 scipy==1.6.2 scanpy==1.7.0 anndata==0.7.6 sklearn tensorflow==1.14.0 %prep %autosetup -n SpaDecon-1.1.2 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-SpaDecon -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue Jun 20 2023 Python_Bot - 1.1.2-1 - Package Spec generated